139 research outputs found
Functional Characterization of CLPTM1L as a Lung Cancer Risk Candidate Gene in the 5p15.33 Locus
Cleft Lip and Palate Transmembrane Protein 1-Like (CLPTM1L), resides in a region of chromosome 5 for which copy number gain has been found to be the most frequent genetic event in the early stages of non-small cell lung cancer (NSCLC). This locus has been found by multiple genome wide association studies to be associated with lung cancer in both smokers and non-smokers. CLPTM1L has been identified as an overexpressed protein in human ovarian tumor cell lines that are resistant to cisplatin, which is the only insight thus far into the function of CLPTM1L. Here we find CLPTM1L expression to be increased in lung adenocarcinomas compared to matched normal lung tissues and in lung tumor cell lines by mechanisms not exclusive to copy number gain. Upon loss of CLPTM1L accumulation in lung tumor cells, cisplatin and camptothecin induced apoptosis were increased in direct proportion to the level of CLPTM1L knockdown. Bcl-xL accumulation was significantly decreased upon loss of CLPTM1L. Expression of exogenous Bcl-xL abolished sensitization to apoptotic killing with CLPTM1L knockdown. These results demonstrate that CLPTM1L, an overexpressed protein in lung tumor cells, protects from genotoxic stress induced apoptosis through regulation of Bcl-xL. Thus, this study implicates anti-apoptotic CLPTM1L function as a potential mechanism of susceptibility to lung tumorigenesis and resistance to chemotherapy
Modelling malaria treatment practices in Bangladesh using spatial statistics
<p>Abstract</p> <p>Background</p> <p>Malaria treatment-seeking practices vary worldwide and Bangladesh is no exception. Individuals from 88 villages in Rajasthali were asked about their treatment-seeking practices. A portion of these households preferred malaria treatment from the National Control Programme, but still a large number of households continued to use drug vendors and approximately one fourth of the individuals surveyed relied exclusively on non-control programme treatments. The risks of low-control programme usage include incomplete malaria treatment, possible misuse of anti-malarial drugs, and an increased potential for drug resistance.</p> <p>Methods</p> <p>The spatial patterns of treatment-seeking practices were first examined using hot-spot analysis (Local Getis-Ord Gi statistic) and then modelled using regression. Ordinary least squares (OLS) regression identified key factors explaining more than 80% of the variation in control programme and vendor treatment preferences. Geographically weighted regression (GWR) was then used to assess where each factor was a strong predictor of treatment-seeking preferences.</p> <p>Results</p> <p>Several factors including tribal affiliation, housing materials, household densities, education levels, and proximity to the regional urban centre, were found to be effective predictors of malaria treatment-seeking preferences. The predictive strength of each of these factors, however, varied across the study area. While education, for example, was a strong predictor in some villages, it was less important for predicting treatment-seeking outcomes in other villages.</p> <p>Conclusion</p> <p>Understanding where each factor is a strong predictor of treatment-seeking outcomes may help in planning targeted interventions aimed at increasing control programme usage. Suggested strategies include providing additional training for the Building Resources across Communities (BRAC) health workers, implementing educational programmes, and addressing economic factors.</p
Transcriptional Regulation of Human Dual Specificity Protein Phosphatase 1 (DUSP1) Gene by Glucocorticoids
Background: Glucocorticoids are potent anti-inflammatory agents commonly used to treat inflammatory diseases. They convey signals through the intracellular glucocorticoid receptor (GR), which upon binding to ligands, associates with genomic glucocorticoid response elements (GREs) to regulate transcription of associated genes. One mechanism by which glucocorticoids inhibit inflammation is through induction of the dual specificity phosphatase-1 (DUSP1, a.k.a. mitogen-activated protein kinase phosphatase-1, MKP-1) gene. Methodology/Principal Findings: We found that glucocorticoids rapidly increased transcription of DUSP1 within 10 minutes in A549 human lung adenocarcinoma cells. Using chromatin immunoprecipitation (ChIP) scanning, we located a GR binding region between 21421 and 21118 upstream of the DUSP1 transcription start site. This region is active in a reporter system, and mutagenesis analyses identified a functional GRE located between 21337 and 21323. We found that glucocorticoids increased DNase I hypersensitivity, reduced nucleosome density, and increased histone H3 and H4 acetylation within genomic regions surrounding the GRE. ChIP experiments showed that p300 was recruited to the DUSP1 GRE, and RNA interference experiments demonstrated that reduction of p300 decreased glucocorticoid-stimulated DUSP1 gene expression and histone H3 hyperacetylation. Furthermore, overexpression of p300 potentiated glucocorticoid-stimulated activity of a reporter gene containing the DUSP1 GRE, and this coactivation effect was compromised when the histone acetyltransferase domain was mutated. ChIP-reChIP experiments using GR followed by p300 antibodies showed significant enrichment of the DUSP1 GRE upon glucocorticoid treatment, suggesting that GR and p300 are in the same protein complex recruited to the DUSP1 GRE. Conclusions/Significance: Our studies identified a functional GRE for the DUSP1 gene. Moreover, the transcriptional activation of DUSP1 by glucocorticoids requires p300 and a rapid modification of the chromatin structure surrounding the GRE. Overall, understanding the mechanism of glucocorticoid-induced DUSP1 gene transcription could provide insights into therapeutic approaches against inflammatory diseases. © 2010 Shipp et al
Comparative Proteomic Analysis of the PhoP Regulon in Salmonella enterica Serovar Typhi Versus Typhimurium
Background: S. Typhi, a human-restricted Salmonella enterica serovar, causes a systemic intracellular infection in humans (typhoid fever). In comparison, S. Typhimurium causes gastroenteritis in humans, but causes a systemic typhoidal illness in mice. The PhoP regulon is a well studied two component (PhoP/Q) coordinately regulated network of genes whose expression is required for intracellular survival of S. enterica. Methodology/Principal Findings: Using high performance liquid chromatography mass spectrometry (HPLC-MS/MS), we examined the protein expression profiles of three sequenced S. enterica strains: S. Typhimurium LT2, S. Typhi CT18, and S. Typhi Ty2 in PhoP-inducing and non-inducing conditions in vitro and compared these results to profiles of mutants derived from S. Typhimurium LT2 and S. Typhi Ty2. Our analysis identified 53 proteins in S. Typhimurium LT2 and 56 proteins in S. Typhi that were regulated in a PhoP-dependent manner. As expected, many proteins identified in S. Typhi demonstrated concordant differential expression with a homologous protein in S. Typhimurium. However, three proteins (HlyE, STY1499, and CdtB) had no homolog in S. Typhimurium. HlyE is a pore-forming toxin. STY1499 encodes a stably expressed protein of unknown function transcribed in the same operon as HlyE. CdtB is a cytolethal distending toxin associated with DNA damage, cell cycle arrest, and cellular distension. Gene expression studies confirmed up-regulation of mRNA of HlyE, STY1499, and CdtB in S. Typhi in PhoP-inducing conditions. Conclusions/Significance: This study is the first protein expression study of the PhoP virulence associated regulon using strains of Salmonella mutant in PhoP, has identified three Typhi-unique proteins (CdtB, HlyE and STY1499) that are not present in the genome of the wide host-range Typhimurium, and includes the first protein expression profiling of a live attenuated bacterial vaccine studied in humans (Ty800)
Ebola Virus Neutralizing Antibodies Detectable in Survivors of theYambuku, Zaire Outbreak 40 Years after Infection.
The first reported outbreak of Ebola virus disease occurred in 1976 in Yambuku, Democratic Republic of Congo. Antibody responses in survivors 11 years after infection have been documented. However, this report is the first characterization of anti-Ebola virus antibody persistence and neutralization capacity 40 years after infection. Using ELISAs we measured survivor's immunological response to Ebola virus Zaire (EBOV) glycoprotein and nucleoprotein, and assessed VP40 reactivity. Neutralization of EBOV was measured using a pseudovirus approach and plaque reduction neutralization test with live EBOV. Some survivors from the original EBOV outbreak still harbor antibodies against all 3 measures. Interestingly, a subset of these survivors' serum antibodies could still neutralize live virus 40 years postinitial infection. These data provide the longest documentation of both anti-Ebola serological response and neutralization capacity within any survivor cohort, extending the known duration of response from 11 years postinfection to at least 40 years after symptomatic infection
The Human Phenotype Ontology in 2024: phenotypes around the world.
The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs
Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care
Genetic drivers of heterogeneity in type 2 diabetes pathophysiology
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p
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